Research: Millions of amateur and professional endurance runners already use online platforms for tracking their performance and progress. They usually use smartwatches or smartphones to track their position via GPS or their heartrate using PPG sensors. Apart from tracking and adapting the training plan, the data captured of all the runners is usually not further processed.

The goal of my research is to use this kind of data for personalized, data-driven recommendation systems. On the one hand, I want to extend the parameters being captured during running by integrating inertial measurement units into the soles of running shoes. Thus, also foot kinematic parameters can be measured. On the other hand, I want to create a personalized running shoe recommendation system using all the different data sources, which helps especially amateur runners with the choice of a suiting running shoe. Besides, I want to use the data for developing a personalized route recommendation system. This system helps runners to find personalized routes in not familiar locations.

Teaching: Apart from my research work, I am coach of the Innovation lab for Wearable and Ubiquitous Computing. In this course, we create innovative prototypes using agile development techniques in cooperation with industry partners. For more information, follow this link.

Since 05/2017

Researcher at the Machine Learning and Data Analytics Lab
Friedrich-Alexander University of Erlangen-Nürnberg

01/2016-04/2017

Researcher at the Pattern Recognition Lab
Friedrich-Alexander University of Erlangen-Nürnberg